Senior AI Developer (Automators)
Remote Poland, PolskaKey offer highlights
Min. 3 years of experience
Backend: Java / .NET / Node / Python
DevOps / Cloud: AWS, Azure, Docker, Kubernetes
Hybrid model - partly remote
QA: manual / automated testing
Description
We are building and maintaining one of the largest OTT platform test automation frameworks, serving millions of customers across streaming TV platforms. The team develops a Java/Appium-based automation framework for Android TV devices and is actively expanding it with AI-powered tooling. We are looking for a Senior AI Developer. This is a hybrid role combining the design and development of AI-powered internal tools with hands-on test automation engineering skills. The ideal candidate is a software engineer who understands both QA automation and modern LLM/RAG systems — and can translate test engineering problems into practical AI solutions.
What we offer
Global Relocation - (Relocation options; Experience in an international environment; Cross-cultural experience)
Recognition and Evaluation - (Feedback culture; Regular appraisals)
Time Off - (Annual holiday - 20 or 26 days. The duration of the leave depends on the overall seniority; Occasional leave - 1 or 2 days/ depending on the circumstances; Child care leave - 2 days or 16 hours per year; Absence due to force majeure - 2 days or 16 hours per year; Maternity Leave - 20 weeks; Parental Leave - 41 weeks; Paternity Leave - 14 days)
Luxoft Training Center - (Expert-led tech courses covering basic to advanced topics; Internal instructor-led soft skills courses; Comprehensive in-house self-learning resources for both soft and hard skills; Access to external self-learning libraries like ProQuest eBook and Udemy for Business; Cloud Programs: MS Cloud Academy, AWS Partner Academy, Google Cloud Academy; Custom Learning Programs: upskilling, reskilling, technical mentorship; Leadership Programs for Managers)
Well-being and Work-life Balance - (Multisport card; Possibility to order Multisport card at the corporate rate for family members; LuxGood Program: wellbeing seminars, contests, relaxation sessions, yoga sessions, etc.; One Team Program: Buddy for each New Joiner; seminars, meeting and workplace space to support integration with local community and culture; “Hire me” workshops for partners; Preferential banking offer; Preferential car leasing offer; Cafeteria program discounts for shops, cinema tickets, holiday offers; Luxoft Social Benefit Fund: sport and recreation benefits, the possibility to receive financial support)
Health Care - (Private Healthcare Insurance with unlimited access to specialists; Full dental support; Travel Insurance; Possibility to add private healthcare coverage for family members at the corporate rate; Life insurance at the corporate rate for employees and family members, including payment of the basic package for the employee by the employer; Reimbursement for corrective glasses)
Company Events and Friendly Environment - (Many fun social activities organized by the Luxoft team offline in your city; Online entertainment events for whole company and local team events; A workplace where you’re treated with respect within a multicultural team)
Internal Mobility - (Rotation between projects and accounts; New career opportunities)
Self-Learning Library
CSR Projects
Other
Languages: English: C1 Advanced
Seniority: Senior
Requirements
AWS Bedrock — hands-on: model access, Knowledge Bases, Lambda integration (primary AI platform)
AI agents & Agentic tooling — practical knowledge of designing and operating AI agents, including agentic workflows, reusable skills, rules/guardrails, commands, and multi-tool/multi-agent orchestration
RAG pipeline — end-to-end implementation: chunking, embedding, vector indexing, retrieval, generation
Prompt engineering — zero-shot, few-shot, chain-of-thought, structured output (JSON mode), multi-turn
Vector databases — working knowledge of OpenSearch, Pinecone, or Faiss; understands vector vs. graph DB difference
LLM guardrails — input/output filtering, hallucination mitigation strategies
Fine-tuning vs. RAG — ability to reason through which approach fits a given problem
LLM orchestration — LangChain, LangGraph, or LlamaIndex
Embeddings — understands semantic similarity; experience with Amazon Titan Embed or equivalent
Python — for Lambda functions, AI pipeline scripting, and data processing
Java — 3+ years of hands-on test automation development
Appium / UiAutomator2 — mobile/Android UI automation
Android / ADB — device management, test execution
ReportPortal or equivalent test reporting tool
REST API — concepts and hands-on usage
Jenkins / CI-CD — pipeline debugging and integration
AWS — S3, Lambda, API Gateway, IAM, OpenSearch Serverless
Docker — containerized test execution environments
Cursor IDE advanced features — .cursorrules, memory-bank context files, MCP server integration, and agentic triage workflows
Android TV platforms — STB / embedded device testing experience (Fire TV, Roku, or similar)
QMetry (QTM4J) — test management integrated with Jira
Streamlit — for building internal AI dashboards
DSPy — programmatic prompt optimization
AWS SageMaker / MLflow — model evaluation and experiment tracking
Kotlin — for tooling alongside Java
Responsibilities
Design and implement AI-powered solutions focused on:
Automated test failure triage — LLM + RAG pipeline classifying ReportPortal failures (logs, stack traces, screenshots) into structured categories (PRODUCT_BUG, AUTOMATION_BUG, SYSTEM_ISSUE) using AWS Bedrock + Claude
AI-based Change-Based Testing (CBT) — LLM-driven test case selection using semantic similarity between code changes and test coverage
AI test case generation from feature specs, Jira tickets, and Confluence documentation
Build and maintain end-to-end RAG pipelines: document ingestion → chunking → embedding → OpenSearch Serverless vector store → retrieval → LLM response generation
Develop AWS Lambda functions (Python 3.12) and API Gateway REST endpoints to integrate AI capabilities into CI/CD pipelines
Apply prompt engineering best practices (system prompts, structured JSON output, guardrails) and drive continuous evaluation of LLM solution accuracy
Use Cursor IDE with MCP integrations, agentic workflows, and context/rules files to accelerate test code generation and maintenance
Write, maintain, and expand automated test suites in Java (Appium / UiAutomator2) for Android TV platforms
Develop and maintain functional, regression, NFR, and CBT test suites
Triage and resolve test failures in ReportPortal; integrate AI triage results with QMetry (QTM4J)
Support CI/CD pipeline health — participate in Nightly Build, RC, and release automation runs via Jenkins
Contribute to framework codebase improvements — bug fixes, refactoring, enhancements
Participate in Kanban ceremonies and PI planning under the ART team
Present AI solution demos to stakeholders and engineering leadership
Document AI system architecture, RAG pipelines, and tools in Confluence
Keywords / Skills